#!/usr/bin/env python3

import re
import os
import argparse
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker

from tools import find_all_files, group_files, csv2numpy


def smooth(y, radius, mode='two_sided', valid_only=False):
    '''Smooth signal y, where radius is determines the size of the window.

    mode='twosided':
        average over the window [max(index - radius, 0), min(index + radius, len(y)-1)]
    mode='causal':
        average over the window [max(index - radius, 0), index]
    valid_only: put nan in entries where the full-sized window is not available
    '''
    assert mode in ('two_sided', 'causal')
    if len(y) < 2 * radius + 1:
        return np.ones_like(y) * y.mean()
    elif mode == 'two_sided':
        convkernel = np.ones(2 * radius + 1)
        out = np.convolve(y, convkernel, mode='same') / \
            np.convolve(np.ones_like(y), convkernel, mode='same')
        if valid_only:
            out[:radius] = out[-radius:] = np.nan
    elif mode == 'causal':
        convkernel = np.ones(radius)
        out = np.convolve(y, convkernel, mode='full') / \
            np.convolve(np.ones_like(y), convkernel, mode='full')
        out = out[:-radius + 1]
        if valid_only:
            out[:radius] = np.nan
    return out


COLORS = ([
    # deepmind style
    '#0072B2',
    '#009E73',
    '#D55E00',
    '#CC79A7',
    # '#F0E442',
    '#d73027',  # RED
    # built-in color
    'blue', 'red', 'pink', 'cyan', 'magenta', 'yellow', 'black', 'purple',
    'brown', 'orange', 'teal', 'lightblue', 'lime', 'lavender', 'turquoise',
    'darkgreen', 'tan', 'salmon', 'gold', 'darkred', 'darkblue', 'green',
    # personal color
    '#313695',  # DARK BLUE
    '#74add1',  # LIGHT BLUE
    '#f46d43',  # ORANGE
    '#4daf4a',  # GREEN
    '#984ea3',  # PURPLE
    '#f781bf',  # PINK
    '#ffc832',  # YELLOW
    '#000000',  # BLACK
])


def plot_ax(
    ax,
    file_lists,
    legend_pattern=".*",
    xlabel=None,
    ylabel=None,
    title=None,
    xlim=None,
    xkey='env_step',
    ykey='rew',
    smooth_radius=0,
    shaded_std=True,
    legend_outside=False,
):
    def legend_fn(x):
        # return os.path.split(os.path.join(
        #     args.root_dir, x))[0].replace('/', '_') + " (10)"
        return re.search(legend_pattern, x).group(0)

    legneds = map(legend_fn, file_lists)
    # sort filelist according to legends
    file_lists = [f for _, f in sorted(zip(legneds, file_lists))]
    legneds = list(map(legend_fn, file_lists))

    for index, csv_file in enumerate(file_lists):
        csv_dict = csv2numpy(csv_file)
        x, y = csv_dict[xkey], csv_dict[ykey]
        y = smooth(y, radius=smooth_radius)
        color = COLORS[index % len(COLORS)]
        ax.plot(x, y, color=color)
        if shaded_std and ykey + ':shaded' in csv_dict:
            y_shaded = smooth(csv_dict[ykey + ':shaded'], radius=smooth_radius)
            ax.fill_between(x, y - y_shaded, y + y_shaded, color=color, alpha=.2)

    ax.legend(legneds, loc=2 if legend_outside else None,
              bbox_to_anchor=(1, 1) if legend_outside else None)
    ax.xaxis.set_major_formatter(mticker.EngFormatter())
    if xlim is not None:
        ax.set_xlim(xmin=0, xmax=xlim)
    # add title
    ax.set_title(title)
    # add labels
    if xlabel is not None:
        ax.set_xlabel(xlabel)
    if ylabel is not None:
        ax.set_ylabel(ylabel)


def plot_figure(
    file_lists,
    group_pattern=None,
    fig_length=6,
    fig_width=6,
    sharex=False,
    sharey=False,
    title=None,
    **kwargs,
):
    if not group_pattern:
        fig, ax = plt.subplots(figsize=(fig_length, fig_width))
        plot_ax(ax, file_lists, title=title, **kwargs)
    else:
        res = group_files(file_lists, group_pattern)
        row_n = int(np.ceil(len(res) / 3))
        col_n = min(len(res), 3)
        fig, axes = plt.subplots(row_n, col_n, sharex=sharex, sharey=sharey, figsize=(
            fig_length * col_n, fig_width * row_n), squeeze=False)
        axes = axes.flatten()
        for i, (k, v) in enumerate(res.items()):
            plot_ax(axes[i], v, title=k, **kwargs)
    if title:  # add title
        fig.suptitle(title, fontsize=20)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='plotter')
    parser.add_argument('--fig-length', type=int, default=6,
                        help='matplotlib figure length (default: 6)')
    parser.add_argument('--fig-width', type=int, default=6,
                        help='matplotlib figure width (default: 6)')
    parser.add_argument('--style', default='seaborn',
                        help='matplotlib figure style (default: seaborn)')
    parser.add_argument('--title', default=None,
                        help='matplotlib figure title (default: None)')
    parser.add_argument('--xkey', default='env_step',
                        help='x-axis key in csv file (default: env_step)')
    parser.add_argument('--ykey', default='rew',
                        help='y-axis key in csv file (default: rew)')
    parser.add_argument('--smooth', type=int, default=0,
                        help='smooth radius of y axis (default: 0)')
    parser.add_argument('--xlabel', default='Timesteps',
                        help='matplotlib figure xlabel')
    parser.add_argument('--ylabel', default='Episode Reward',
                        help='matplotlib figure ylabel')
    parser.add_argument(
        '--shaded-std', action='store_true',
        help='shaded region corresponding to standard deviation of the group')
    parser.add_argument('--sharex', action='store_true',
                        help='whether to share x axis within multiple sub-figures')
    parser.add_argument('--sharey', action='store_true',
                        help='whether to share y axis within multiple sub-figures')
    parser.add_argument('--legend-outside', action='store_true',
                        help='place the legend outside of the figure')
    parser.add_argument('--xlim', type=int, default=None,
                        help='x-axis limitation (default: None)')
    parser.add_argument('--root-dir', default='./', help='root dir (default: ./)')
    parser.add_argument(
        '--file-pattern', type=str, default=r".*/test_rew_\d+seeds.csv$",
        help='regular expression to determine whether or not to include target csv '
        'file, default to including all test_rew_{num}seeds.csv file under rootdir')
    parser.add_argument(
        '--group-pattern', type=str, default=r"(/|^)\w*?\-v(\d|$)",
        help='regular expression to group files in sub-figure, default to grouping '
        'according to env_name dir, "" means no grouping')
    parser.add_argument(
        '--legend-pattern', type=str, default=r".*",
        help='regular expression to extract legend from csv file path, default to '
        'using file path as legend name.')
    parser.add_argument('--show', action='store_true', help='show figure')
    parser.add_argument('--output-path', type=str,
                        help='figure save path', default="./figure.png")
    parser.add_argument('--dpi', type=int, default=200,
                        help='figure dpi (default: 200)')
    args = parser.parse_args()
    file_lists = find_all_files(args.root_dir, re.compile(args.file_pattern))
    file_lists = [os.path.relpath(f, args.root_dir) for f in file_lists]
    if args.style:
        plt.style.use(args.style)
    os.chdir(args.root_dir)
    plot_figure(
        file_lists,
        group_pattern=args.group_pattern,
        legend_pattern=args.legend_pattern,
        fig_length=args.fig_length,
        fig_width=args.fig_width,
        title=args.title,
        xlabel=args.xlabel,
        ylabel=args.ylabel,
        xkey=args.xkey,
        ykey=args.ykey,
        xlim=args.xlim,
        sharex=args.sharex,
        sharey=args.sharey,
        smooth_radius=args.smooth,
        shaded_std=args.shaded_std,
        legend_outside=args.legend_outside)
    if args.output_path:
        plt.savefig(args.output_path,
                    dpi=args.dpi, bbox_inches='tight')
    if args.show:
        plt.show()
